import os
import logging

logging.basicConfig(level=logging.INFO)

pj_root = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../')

task = 'val'  # val, valall, test

if task == 'val' or task == 'valall':
    dataset = 'val'  # these tasks share one dataset
elif task == 'test':
    dataset = 'test'

kfold = True
kfold_k = 4

import xgboost
model = xgboost.XGBClassifier
model_para = {
    'objective': 'rank:pairwise',
    'n_estimators': 74,
    'scale_pos_weight': 10,
    'learning_rate': 0.3,
}

# from sklearn.linear_model import LogisticRegression
# model = LogisticRegression
# model_para = {}
